1. Field
This disclosure is generally related to detecting malicious insider activities. More specifically, this disclosure is related to a probability model for detecting malicious activity performed by insiders within an organization.
2. Related Art
Malicious insiders are an increasing threat to many organizations. People authorized to access internal information may disrupt the organization's operations or leak sensitive information to outside parties. As a result, collecting and monitoring work practice data within organizations is becoming prevalent. This work practice data includes many typical activities of PC users, such as logging on/off, accessing web sites, sending and receiving emails, and accessing external devices or files. Each activity is called a “domain” or a “modality.” For example, domains may include logon domain and email domain. One may detect malicious intent within an organization before the malicious activity occurs by analyzing this data and detecting anomalies. Currently, this analysis is limited to a single domain at a time. Typically, one detects anomalies or outliers separately within each domain. Some approaches combine anomaly scores in an ad hoc manner (for example, by ignoring users who are outliers in only one domain). Users who are not outliers in any of the domains may never be labeled as outliers by these analysis methods.